Automated cell segmentation for microscopy cell images has recently become an initial step
for further image analysis in cell biology. However, microscopy cell images are easily …

Purpose The utility of fluorescence microscopy imaging comes with the challenge of low
resolution acquisitions, which severely limits information extraction and quantitative …

Phase contrast and differential interference contrast, which are used to capture microscopy
images of living cells, contain a few artifacts such as halo and shadow-cast effect. Removing …

An efficient segmentation technique based on the use of a modified k-Means algorithm and
the Otsu's thresholding method is improved through a non-linear restoration of microscope …

This thesis introduces new solutions to the problem of image restoration in biomedical fields.
The confocal microscope is a relatively new imaging technique that is emerging as a …

There are numerous segmentation methods for gray level microscope cell images, however
in some situations the texture features and roughness are not as relevant as the color for the …

Three dimensional optical microscopy images are noisy and blurred, have nonuniform
background, and contain objects which do not usually have sharp edges or may have noise …

Abstract The advent of Fluorescence Microscopy over the last few years have dramatically
improved the problem of visualization and tracking of specific cellular objects for biological …

The expectation-maximization (EM) algorithm for maximum-likelihood image recovery
converges very slowly. Thus, the ordered subsets EM (OS-EM) algorithm has been widely …

Instant Image Denoising Plugin for ImageJ using Convolutional Neural Networks Page 1
MW2A.3.pdf Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT …